Close Menu

NEW YORK – A molecular method to identify bacterial infections and detect their antibiotic resistance phenotypes is generalizable to many types of bacteria and can produce results from clinical blood culture samples in about four hours, according to a new study.

The technique, called combined genotypic and phenotypic AST though RNA detection (GoPhAST-R), uses NanoString's enzyme-free hybridization-based technology, and the firm now intends to commercialize the method through an industry partnership.

Get the full story with
GenomeWeb Premium

Only $95 for the
first 90 days*

GenomeWeb Premium gives you:
✔ Full site access
✔ Interest-based email alerts
✔ Access to archives

Never miss another important industry story.

Try GenomeWeb Premium now.

You may already have institutional access!

Check if I qualify.

Already a GenomeWeb or 360Dx Premium member?
Login Now.

*Before your trial expires, we’ll put together a custom quote with your long-term premium options.

Not ready for premium?

Register for Free Content
You can still register for access to our free content.

The Washington Post reports on researchers' efforts to determine the effect of an increasingly common SARS-CoV-2 mutation.

Florida Politics reports Florida's law barring life, long-term care, and disability insurers from using genetic information in coverage decisions went into effect at the beginning of July.

A new analysis finds a link between popular media coverage of a scientific study and how often that paper is cited.

In Nature this week: CRISPR approaches to editing plant genomes, way to speed up DNA-PAINT, and more.

Jul
14
Sponsored by
Agilent

This webinar will describe a rapid metagenomics assay under development for human pathogens, including the SARS-CoV-2 coronavirus.

Jul
16
Sponsored by
NanoString

Join this webinar to learn how spatial resolution of gene expression in tumor tissue reveals new insights in biomarker discovery and therapeutic response. 

Aug
13
Sponsored by
10x Genomics

This webinar will discuss a study that combined single-cell gene expression and spatial gene expression to understand the evolution of sepsis in the kidney at the cellular and molecular level.